Articles — Two-column

Inconel 718 is the most employed superalloy in the industry and it is often found in aerospace engines and power generation turbines. Superalloys are known as one of the most difficult group of materials to machine and therefore, tool material, tool geometry and cutting parameters should be carefully selected. Numerous researches have proven the enhanced productivity in turning of ceramic tools compared to carbide ones, while considerably less information is with regard to milling. Moreover, no knowledge has been developed about machining holes with this type of tools. More research on different machining techniques like circular ramping is critical to expand the productivity improvements that ceramics offer. This paper initially reviews prior work about ceramic tools. Then, a 3D simulation and a number of experiments with SiAlON round inserts have been carried out to evaluate the effect of the cutting speed and pitch on the tool wear and chip generation. The results show that three different types of chips are generated as well as that there are three potential wear zones. Top slice wear was identified as the most critic wear type followed by the notch wear. Flank wear and adhesion were also found in most of the tests. To conclude with, a 6.6 times more productive process than with carbide tools was achieved. Cet article étudie deux méthodes utilisées dans le cadre du transport humanitaire en cas de crise (désastre, épidémie...). Le Covering Tour Problem se focalise sur l'équité de distribution des vivres, alors que le Capacitated Vehicle Routing Problem se concentre sur l'urgence de la distribution. Nous proposons une nouvelle approche mélangeant ces deux approches pour former une solution à la fois équitable et rapide. Ce article a été rédigé dans le cadre du TER 2014-2015.

Deep learning is a fast growing field in tech that is often described to have limitless potential. This paper describes its history, why the explosion in popularity, and how it works. An example of classifying images of handwritten digits (MNIST) will be explored using a fully connected network and a convolutional neural network. Next, a brief description of the tools necessary for the reader to implement his or her own network. Finally, a view of the state of the art being developed by companies such as Google, Facebook, and Baidu.

This paper describes the creation of the tool to approach to models of dispersion of pollutants, framed under a methodology of software development, which identified the sequence to follow in the life cycle extension development, through an incremental model in which the stages of the project were identified. At each stage a series of activities that helped define inputs and outputs in each was made. According the above in the first stage the functional requirements defined and nonfunctional, then in stage two architecture and graphical interface, followed by the coding stage extension and finally the stage of performance testing and user, in order to improve or correct the functionality of the extension.

In this paper we propose a first version for a computational proposal for Electromagnetic Field (EMF) Pollution for the construction of calculated maps, as a visualization tool for estimating the levels of human exposure to potentially harmful levels of electromagnetic radiation. The computational model includes the necessary mathematics for estimating levels of exposure in any two dimension space point in a map, given a massive set of emitters and its relevant parameters, but also contains adjust considerations using a data set of field measures that would allow the model to adapt to real environmental conditions. This combination of mathematical model and field data also will allow us to skip the use of interpolations an other statistical methods typically used in maps based exclusively on measures. The proposal also specifies the system main features and development methodology in order to achieve an interactive and flexible tool.